!pip install sweetviz
!pip install pandas-profiling
!pip install ydata-profiling
Collecting sweetviz
Downloading sweetviz-2.3.1-py3-none-any.whl (15.1 MB)
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Requirement already satisfied: pandas!=1.0.0,!=1.0.1,!=1.0.2,>=0.25.3 in /usr/local/lib/python3.10/dist-packages (from sweetviz) (1.5.3)
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Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.7->matplotlib>=3.1.3->sweetviz) (1.16.0)
Installing collected packages: sweetviz
Successfully installed sweetviz-2.3.1
Collecting pandas-profiling
Downloading pandas_profiling-3.6.6-py2.py3-none-any.whl (324 kB)
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Collecting ydata-profiling (from pandas-profiling)
Downloading ydata_profiling-4.6.5-py2.py3-none-any.whl (357 kB)
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Collecting visions[type_image_path]==0.7.5 (from ydata-profiling->pandas-profiling)
Downloading visions-0.7.5-py3-none-any.whl (102 kB)
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Requirement already satisfied: numpy<1.26,>=1.16.0 in /usr/local/lib/python3.10/dist-packages (from ydata-profiling->pandas-profiling) (1.25.2)
Collecting htmlmin==0.1.12 (from ydata-profiling->pandas-profiling)
Downloading htmlmin-0.1.12.tar.gz (19 kB)
Preparing metadata (setup.py) ... done
Collecting phik<0.13,>=0.11.1 (from ydata-profiling->pandas-profiling)
Downloading phik-0.12.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (686 kB)
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Collecting seaborn<0.13,>=0.10.1 (from ydata-profiling->pandas-profiling)
Downloading seaborn-0.12.2-py3-none-any.whl (293 kB)
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Collecting multimethod<2,>=1.4 (from ydata-profiling->pandas-profiling)
Downloading multimethod-1.11.2-py3-none-any.whl (10 kB)
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Collecting typeguard<5,>=4.1.2 (from ydata-profiling->pandas-profiling)
Downloading typeguard-4.1.5-py3-none-any.whl (34 kB)
Collecting imagehash==4.3.1 (from ydata-profiling->pandas-profiling)
Downloading ImageHash-4.3.1-py2.py3-none-any.whl (296 kB)
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Requirement already satisfied: wordcloud>=1.9.1 in /usr/local/lib/python3.10/dist-packages (from ydata-profiling->pandas-profiling) (1.9.3)
Collecting dacite>=1.8 (from ydata-profiling->pandas-profiling)
Downloading dacite-1.8.1-py3-none-any.whl (14 kB)
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Collecting tangled-up-in-unicode>=0.0.4 (from visions[type_image_path]==0.7.5->ydata-profiling->pandas-profiling)
Downloading tangled_up_in_unicode-0.2.0-py3-none-any.whl (4.7 MB)
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Building wheels for collected packages: htmlmin
Building wheel for htmlmin (setup.py) ... done
Created wheel for htmlmin: filename=htmlmin-0.1.12-py3-none-any.whl size=27080 sha256=3e00bd2c69ff80e7059d02de09a44d9ccb31f140118bc0f9eac2e100100ca0dc
Stored in directory: /root/.cache/pip/wheels/dd/91/29/a79cecb328d01739e64017b6fb9a1ab9d8cb1853098ec5966d
Successfully built htmlmin
Installing collected packages: htmlmin, typeguard, tangled-up-in-unicode, multimethod, dacite, imagehash, visions, seaborn, phik, ydata-profiling, pandas-profiling
Attempting uninstall: seaborn
Found existing installation: seaborn 0.13.1
Uninstalling seaborn-0.13.1:
Successfully uninstalled seaborn-0.13.1
Successfully installed dacite-1.8.1 htmlmin-0.1.12 imagehash-4.3.1 multimethod-1.11.2 pandas-profiling-3.6.6 phik-0.12.4 seaborn-0.12.2 tangled-up-in-unicode-0.2.0 typeguard-4.1.5 visions-0.7.5 ydata-profiling-4.6.5
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!pip install -U dataprep
Collecting dataprep
Downloading dataprep-0.4.5-py3-none-any.whl (9.9 MB)
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Requirement already satisfied: aiohttp<4.0,>=3.6 in /usr/local/lib/python3.10/dist-packages (from dataprep) (3.9.3)
Collecting bokeh<3,>=2 (from dataprep)
Downloading bokeh-2.4.3-py3-none-any.whl (18.5 MB)
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Collecting flask_cors<4.0.0,>=3.0.10 (from dataprep)
Downloading Flask_Cors-3.0.10-py2.py3-none-any.whl (14 kB)
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Requirement already satisfied: soupsieve>1.2 in /usr/local/lib/python3.10/dist-packages (from beautifulsoup4->nbconvert>=5->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets<8.0,>=7.5->dataprep) (2.5)
Requirement already satisfied: webencodings in /usr/local/lib/python3.10/dist-packages (from bleach->nbconvert>=5->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets<8.0,>=7.5->dataprep) (0.5.1)
Requirement already satisfied: sniffio>=1.1 in /usr/local/lib/python3.10/dist-packages (from anyio<4,>=3.1.0->jupyter-server>=1.8->nbclassic>=0.4.7->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets<8.0,>=7.5->dataprep) (1.3.1)
Requirement already satisfied: exceptiongroup in /usr/local/lib/python3.10/dist-packages (from anyio<4,>=3.1.0->jupyter-server>=1.8->nbclassic>=0.4.7->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets<8.0,>=7.5->dataprep) (1.2.0)
Requirement already satisfied: pycparser in /usr/local/lib/python3.10/dist-packages (from cffi>=1.0.1->argon2-cffi-bindings->argon2-cffi->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets<8.0,>=7.5->dataprep) (2.21)
Building wheels for collected packages: sqlalchemy, metaphone
Building wheel for sqlalchemy (setup.py) ... done
Created wheel for sqlalchemy: filename=SQLAlchemy-1.3.24-cp310-cp310-linux_x86_64.whl size=1252696 sha256=c093ab22e2a0bcbf64a7ef4405121aba6a333a6ef3b66d2fb9f0dc9b6080b04b
Stored in directory: /root/.cache/pip/wheels/27/51/b3/3481e88d5a5ba95dd4aafedc9316774d941c4ba61cfb93add8
Building wheel for metaphone (setup.py) ... done
Created wheel for metaphone: filename=Metaphone-0.6-py3-none-any.whl size=13902 sha256=c41cc842c6bd8871de0a5beee19c5ce0cdec2a0cb8cfd3688f7585e02364d06a
Stored in directory: /root/.cache/pip/wheels/23/dd/1d/6cdd346605db62bde1f60954155e9ce48f4681c243f265b704
Successfully built sqlalchemy metaphone
Installing collected packages: regex, python-stdnum, python-crfsuite, pure_eval, ply, metaphone, executing, sqlalchemy, rapidfuzz, pydantic, jsonpath-ng, jinja2, jedi, asttokens, varname, bokeh, flask_cors, dataprep
Attempting uninstall: regex
Found existing installation: regex 2023.12.25
Uninstalling regex-2023.12.25:
Successfully uninstalled regex-2023.12.25
Attempting uninstall: sqlalchemy
Found existing installation: SQLAlchemy 2.0.28
Uninstalling SQLAlchemy-2.0.28:
Successfully uninstalled SQLAlchemy-2.0.28
Attempting uninstall: pydantic
Found existing installation: pydantic 2.6.4
Uninstalling pydantic-2.6.4:
Successfully uninstalled pydantic-2.6.4
Attempting uninstall: jinja2
Found existing installation: Jinja2 3.1.3
Uninstalling Jinja2-3.1.3:
Successfully uninstalled Jinja2-3.1.3
Attempting uninstall: bokeh
Found existing installation: bokeh 3.3.4
Uninstalling bokeh-3.3.4:
Successfully uninstalled bokeh-3.3.4
ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
torch 2.2.1+cu121 requires nvidia-cublas-cu12==12.1.3.1; platform_system == "Linux" and platform_machine == "x86_64", which is not installed.
torch 2.2.1+cu121 requires nvidia-cuda-cupti-cu12==12.1.105; platform_system == "Linux" and platform_machine == "x86_64", which is not installed.
torch 2.2.1+cu121 requires nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == "Linux" and platform_machine == "x86_64", which is not installed.
torch 2.2.1+cu121 requires nvidia-cuda-runtime-cu12==12.1.105; platform_system == "Linux" and platform_machine == "x86_64", which is not installed.
torch 2.2.1+cu121 requires nvidia-cudnn-cu12==8.9.2.26; platform_system == "Linux" and platform_machine == "x86_64", which is not installed.
torch 2.2.1+cu121 requires nvidia-cufft-cu12==11.0.2.54; platform_system == "Linux" and platform_machine == "x86_64", which is not installed.
torch 2.2.1+cu121 requires nvidia-curand-cu12==10.3.2.106; platform_system == "Linux" and platform_machine == "x86_64", which is not installed.
torch 2.2.1+cu121 requires nvidia-cusolver-cu12==11.4.5.107; platform_system == "Linux" and platform_machine == "x86_64", which is not installed.
torch 2.2.1+cu121 requires nvidia-cusparse-cu12==12.1.0.106; platform_system == "Linux" and platform_machine == "x86_64", which is not installed.
torch 2.2.1+cu121 requires nvidia-nccl-cu12==2.19.3; platform_system == "Linux" and platform_machine == "x86_64", which is not installed.
torch 2.2.1+cu121 requires nvidia-nvtx-cu12==12.1.105; platform_system == "Linux" and platform_machine == "x86_64", which is not installed.
bigframes 0.24.0 requires sqlalchemy<3.0dev,>=1.4, but you have sqlalchemy 1.3.24 which is incompatible.
ipython-sql 0.5.0 requires sqlalchemy>=2.0, but you have sqlalchemy 1.3.24 which is incompatible.
panel 1.3.8 requires bokeh<3.4.0,>=3.2.0, but you have bokeh 2.4.3 which is incompatible.
ydata-profiling 4.6.5 requires pydantic>=2, but you have pydantic 1.10.14 which is incompatible.
Successfully installed asttokens-2.4.1 bokeh-2.4.3 dataprep-0.4.5 executing-0.8.3 flask_cors-3.0.10 jedi-0.19.1 jinja2-3.0.3 jsonpath-ng-1.6.1 metaphone-0.6 ply-3.11 pure_eval-0.2.2 pydantic-1.10.14 python-crfsuite-0.9.8 python-stdnum-1.19 rapidfuzz-2.15.2 regex-2021.11.10 sqlalchemy-1.3.24 varname-0.8.3
# import libraries
import pandas as pd
import numpy as np
import seaborn as sns
from ydata_profiling import ProfileReport
import sweetviz as sv
# read dataset
zomato=pd.read_csv("/content/zomato.csv",encoding='latin')
# check for null values
zomato.isna().sum()/zomato.shape[0]/100
Restaurant ID 0.000000 Restaurant Name 0.000000 Country Code 0.000000 City 0.000000 Address 0.000000 Locality 0.000000 Locality Verbose 0.000000 Longitude 0.000000 Latitude 0.000000 Cuisines 0.000009 Average Cost for two 0.000000 Currency 0.000000 Has Table booking 0.000000 Has Online delivery 0.000000 Is delivering now 0.000000 Switch to order menu 0.000000 Price range 0.000000 Aggregate rating 0.000000 Rating color 0.000000 Rating text 0.000000 Votes 0.000000 dtype: float64
# shown first 5 rows
zomato.head(5)
| Restaurant ID | Restaurant Name | Country Code | City | Address | Locality | Locality Verbose | Longitude | Latitude | Cuisines | ... | Currency | Has Table booking | Has Online delivery | Is delivering now | Switch to order menu | Price range | Aggregate rating | Rating color | Rating text | Votes | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 6317637 | Le Petit Souffle | 162 | Makati City | Third Floor, Century City Mall, Kalayaan Avenu... | Century City Mall, Poblacion, Makati City | Century City Mall, Poblacion, Makati City, Mak... | 121.027535 | 14.565443 | French, Japanese, Desserts | ... | Botswana Pula(P) | Yes | No | No | No | 3 | 4.8 | Dark Green | Excellent | 314 |
| 1 | 6304287 | Izakaya Kikufuji | 162 | Makati City | Little Tokyo, 2277 Chino Roces Avenue, Legaspi... | Little Tokyo, Legaspi Village, Makati City | Little Tokyo, Legaspi Village, Makati City, Ma... | 121.014101 | 14.553708 | Japanese | ... | Botswana Pula(P) | Yes | No | No | No | 3 | 4.5 | Dark Green | Excellent | 591 |
| 2 | 6300002 | Heat - Edsa Shangri-La | 162 | Mandaluyong City | Edsa Shangri-La, 1 Garden Way, Ortigas, Mandal... | Edsa Shangri-La, Ortigas, Mandaluyong City | Edsa Shangri-La, Ortigas, Mandaluyong City, Ma... | 121.056831 | 14.581404 | Seafood, Asian, Filipino, Indian | ... | Botswana Pula(P) | Yes | No | No | No | 4 | 4.4 | Green | Very Good | 270 |
| 3 | 6318506 | Ooma | 162 | Mandaluyong City | Third Floor, Mega Fashion Hall, SM Megamall, O... | SM Megamall, Ortigas, Mandaluyong City | SM Megamall, Ortigas, Mandaluyong City, Mandal... | 121.056475 | 14.585318 | Japanese, Sushi | ... | Botswana Pula(P) | No | No | No | No | 4 | 4.9 | Dark Green | Excellent | 365 |
| 4 | 6314302 | Sambo Kojin | 162 | Mandaluyong City | Third Floor, Mega Atrium, SM Megamall, Ortigas... | SM Megamall, Ortigas, Mandaluyong City | SM Megamall, Ortigas, Mandaluyong City, Mandal... | 121.057508 | 14.584450 | Japanese, Korean | ... | Botswana Pula(P) | Yes | No | No | No | 4 | 4.8 | Dark Green | Excellent | 229 |
5 rows × 21 columns
# generate standard profiling report
profile=ProfileReport(zomato,title="Zomato Report")
profile
Report=sv.analyze(zomato)
Report.show_html(filepath='SWEETVIZ_REPORT.html',open_browser=True,layout='widescreen',scale=None)
/usr/local/lib/python3.10/dist-packages/sweetviz/graph.py:33: UserWarning: Glyph 140 (\x8c) missing from current font. figure.savefig(as_raw_bytes, format='png', transparent=True) /usr/local/lib/python3.10/dist-packages/sweetviz/graph.py:33: UserWarning: Glyph 140 (\x8c) missing from current font. figure.savefig(as_raw_bytes, format='png', transparent=True)
Report SWEETVIZ_REPORT.html was generated! NOTEBOOK/COLAB USERS: the web browser MAY not pop up, regardless, the report IS saved in your notebook/colab files.
Report.show_html(filepath='SWEETVIZ_REPORT.html',open_browser=True,layout='widescreen',scale=None)
Report SWEETVIZ_REPORT.html was generated! NOTEBOOK/COLAB USERS: the web browser MAY not pop up, regardless, the report IS saved in your notebook/colab files.